Learning With Errors (LWE) is a problem in computer science and cryptography that involves solving linear equations with some noise or errors. The goal is to find a secret vector given a set of equations that are perturbed by random errors. This problem is believed to be hard for classical computers, making it a useful foundation for secure cryptographic systems. LWE has applications in various areas, including homomorphic encryption and post-quantum cryptography. These applications leverage the hardness of the LWE problem to create secure communication methods that can withstand potential threats from quantum computers, ensuring data privacy and integrity.